Trading_bot

A simple bot using ccxt library to trade on centralized exchanges (CEX) such as Binance and KuCoin. The aim is to test different trading strategies automatically.

Project Structure

• Exchange_trade.py: Contains the Exchange class and helper functions to connect and interact with CEX APIs via ccxt. This module handles market data, trading orders, and risk management.
• Sharing_data.py: Provides utilities for logging, file operations, and JSON handling to share data between modules.
• Trading_main.py: Implements the main trading logic, including backtesting and live trading process orchestration.
• Trading_tools.py: Offers various technical analysis tools, such as MACD, Heikin Ashi calculations, order block identification, and Fair Value Gap (FVG) detection.
• streamlit_app.py: A web dashboard built with Streamlit for visualizing trading performance, data analytics, and real-time monitoring.
• webhook_receiver.py: A Flask-based webhook handler to automatically deploy code updates upon new commits.
• Trading_ai.py: Provides AI-based analysis of market data using the OpenAI API to process and return structured JSON from files in the data folder.

Repository Map

Trading_bot/
├── .gitignore
├── LICENSE
├── README.md
├── requirements.txt
├── Exchange_trade.py
├── Sharing_data.py
├── Trading_main.py
├── Trading_tools.py
├── streamlit_app.py
├── Trading_ai.py
└── webhook_receiver.py

Example Usage

• Run simulation/backtesting: python Trading_main.py

• Launch the trading dashboard: streamlit run streamlit_app.py

• Launch the webhook receiver (main file for auto-deploy): python webhook_receiver.py

Getting Started

1. Install dependencies: pip install -r requirements.txt

2. Run the main trading script: python Trading_main.py

3. Start the Streamlit app: streamlit run streamlit_app.py

Module Details

• Exchange_trade.py: Implements the Exchange class to manage connections to centralized exchanges. It handles market data fetching, order execution, balance management, and error handling via the ccxt library.
• Sharing_data.py: Contains logging, data persistence, and file management utilities. Nearly all modules use this to record key events, share JSON data, and maintain logs.
• Trading_tools.py: Provides technical analysis functions—including MACD, EMA, Heikin Ashi, order block, and Fair Value Gap (FVG) calculations—to generate reliable trading signals.
• Trading_main.py: Orchestrates the trading process by combining market data (from Exchange_trade.py), trading signals (via Trading_tools.py), and order management. It manages both backtesting and live trading routines.
• Trading_ai.py: Integrates with the OpenAI API to analyze historical market data stored as JSON in the data folder, returning structured JSON output that can inform trading decisions.
• streamlit_app.py: Offers a real-time web dashboard built with Streamlit where trading performance, data analytics, and system logs are visualized.
• webhook_receiver.py: Listens for GitHub webhook events and automates deployment updates. It pulls the latest commits and restarts the Streamlit app and trading scripts accordingly.